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SCHUMACHER ET AL.
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Tropical Cloud Heating Profiles: Analysis from KWAJEX
COURTNEY SCHUMACHER
Department of Atmospheric Sciences, Texas A&M University, College Station, Texas
PAUL E. CIESIELSKI
Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado
MINGHUA H. ZHANG
Institute for Terrestrial and Planetary Atmospheres, Marine Sciences Research Center, Stony Brook University,
Stony Brook, New York
(Manuscript received 5 June 2007, in final form 13 March 2008)
ABSTRACT
Diabatic heating (or Q1) profiles associated with specific cloud types are produced by matching synoptic
cloud observations with a sounding budget analysis during the Tropical Rainfall Measuring Mission
(TRMM) Kwajalein Experiment (KWAJEX), which took place in the Marshall Islands from late July
through mid-September 1999. Fair-weather cumulus clouds produce up to 1 K day⫺1 of heating below 850
hPa and are associated with cooling throughout much of the rest of the troposphere. Cumulus congestus
clouds produce heating on the order of 1 K day⫺1 up to 575 hPa and cooling in the mid- to upper
troposphere. Cumulonimbus clouds produce heating through the depth of the troposphere, with a maximum
of 3.7 K day⫺1 near 550 hPa. Cloud types indicating widespread rain (stratus or cumulus fractus of bad
weather at low levels and nimbostratus at midlevels) have the largest and most elevated heating, with values
⬎10 K day⫺1 above 600 hPa. Other mid- and high-level cloud types are shown to be consistent with
area-averaged rain rates and Q1 profiles. Profiles of the divergence and apparent moisture sink (or Q2) for
convective clouds are also analyzed and are shown to be consistent with the physics of the heating profiles
just described.
1. Introduction
The diabatic heating associated with tropical cloud
systems is often considered a driver of large-scale circulations in the tropics and extratropics (e.g., Hartmann
et al. 1984). Budget studies allow the computation of
bulk heating profiles associated with the ensemble of
tropical convection over large regions, typically a
sounding network covering an area ⬎100 000 km2 (e.g.,
Reed and Recker 1971). However, it is much more difficult to observe the heating profile associated with a
particular cloud type.
This work is an extension of Schumacher et al.
(2007), who focused on characterizing the diabatic
heating from the Tropical Rainfall Measuring Mission
(TRMM) Kwajalein Experiment (KWAJEX) and two
other TRMM field campaigns using sounding budget
analyses. However, in Schumacher et al. (2007) the role
of particular cloud types in diabatic heating variations
remained speculative. This study attempts to isolate the
heating associated with different tropical clouds, with
emphasis on fair-weather cumulus, cumulus congestus,
and cumulonimbus types, by matching visual cloud observations with a sounding budget analysis over the
west Pacific intertropical convergence zone (ITCZ)
during KWAJEX.
2. Data and methods
Corresponding author address: Courtney Schumacher, Department of Atmospheric Sciences, Texas A&M University, 3150
TAMU, College Station, TX 77843-3150.
E-mail: [email protected]
DOI: 10.1175/2008MWR2275.1
© 2008 American Meteorological Society
KWAJEX took place in the Marshall Islands (7°–
10°N, 166°–169°E; Fig. 1) from 24 July to 15 September
1999 with the purpose of studying convective processes
over the tropical ocean and how these processes relate
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MONTHLY WEATHER REVIEW
FIG. 1. The variational analysis domain (thick circle) for
KWAJEX. Sounding sites are indicated by triangles. The radar
and cloud observations were located at Kwajalein Island (filled
triangle). Dotted lines indicate the outlines of atolls (i.e., coral
islands enclosing a lagoon); the rest of the region is open ocean.
to National Aeronautic and Space Administration
(NASA) TRMM satellite retrievals (Yuter et al. 2005).
Kwajalein and the surrounding atolls are composed of
very small islands with negligible land surface, such that
the region can be considered open ocean. Further,
while Kwajalein represents only one location in the
ITCZ, we postulate that the diabatic heating associated
with specified cloud types will be qualitatively similar in
other oceanic locations.
During the field campaign, cloud observations were
made by KWAJEX scientists 3 times daily [2000, 0100,
and 0600 UTC (0800, 1300, and 1800 LT, respectively)]
from the operations center on Kwajalein Island (filled
VOLUME 136
triangle in Fig. 1). Clouds were classified according to
the World Meteorological Organization’s (WMO’s)
synoptic code (WMO 1974) into 10 types (including no
cloud) at each of the following height levels: low (cloud
bases ⬎800 hPa; CL), middle (cloud bases 800–400 hPa;
CM), and high (cloud bases ⬍400 hPa; CH). Cloud bases
were determined by visual estimation. The KWAJEX
observers also followed the WMO’s basis of priorities,
which assigns a priority to each cloud type; only the
highest priority cloud is reported at each level regardless of the area covered.1 Therefore, lower-priority
clouds are possibly underestimated using this system.
Cloud-type descriptions and WMO priorities are listed
in Tables 1–3; a value of 1 represents the highest priority. While subjectivity by human observers inherently
limits the accuracy of cloud classifications, temporal averaging is used in this study to minimize potential misclassifications (see also section 3). In addition, digital
photo panoramas for KWAJEX were archived (available online at http://www.atmos.washington.edu/
kwajex/ops-web/cloud_photos).
This study links cloud occurrence to area-averaged
rainfall and diabatic heating (or the apparent heat
source Q1) profiles during KWAJEX. Rainfall is based
on ground radar precipitation maps processed by the
University of Washington (Houze et al. 2004). Yanai et
al. (1973) defined Q1 as
Q1 ⫽
⭸s
⭸共s ␻兲
⫹ ⵱ ⭈ 共sV兲 ⫹
,
⭸t
⭸p
共1兲
where s is the dry static energy, which is equal to the
sum of enthalpy and potential energy (or s ⫽ cpT ⫹ gz).
Overbars represent the average over the budget area.
The variational analysis approach of Zhang and Lin
(1997), which constrains the sounding data to
1
During KWAJEX, only total cloud cover (octa) was recorded,
not the area covered by each cloud type.
TABLE 1. KWAJEX cloud types with low-level bases.
CL
Description
Priority
No. of observations
Frequency (%)
0
1
2
3
4
5
6
7
8
9
No clouds with bases below 800 hPa
Fair-weather cumulus (Cu)
Cumulus congestus (TCu)
Cumulonimbus (Cb) with ill-defined top
Stratocumulus (Sc) from spreading of Cu
Sc not from spreading of Cu
Stratus (St) not of bad weather
St fractus or Cu fractus of bad weather
Cu under Sc
Cb with cirriform top
7
6
5
2
3
6
6
6
4
1
2
33
47
28
0
1
0
10
0
32
1.3
21.6
30.7
18.3
0
0.7
0
6.5
0
20.9
Rain rate
(mm day⫺1)
0.8
3.1
8.6
28.3
7.3
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SCHUMACHER ET AL.
TABLE 2. KWAJEX cloud types with midlevel bases.
CM
Description
Priority
No. of observations
Frequency (%)
0
1
2
3
4
5
6
7
8
9
No clouds with bases between 800 and 400 hPa
Semitransparent altostratus (As)
Thick As or nimbostratus (Ns)
Semitransparent altocumulus (Ac), one level
Semitransparent Ac, one or more levels, variable
Ac invading the sky as it thickens
Ac from spreading of Cu, TCu, or Cb
Opaque Ac, two or more layers or with As or Ns
Ac with turrets
Ac of a chaotic sky
11
1
2
10
8
7
6
5, 9, 10
4
3
36
10
15
8
8
3
9
26
16
22
23.5
6.5
9.8
5.2
5.2
2.0
5.9
17.0
10.5
14.4
satisfy column-integrated budgets of mass, energy, and
moisture, was used to derive the Q1 profiles. The radarderived rainfall was one of the analysis constraints.
Rain rates and Q1 values over the variational analysis
domain were computed for 6-h periods centered on
0000, 0600, 1200, and 1800 UTC. Further details on the
KWAJEX variational analysis and Q1 structures classified by the diurnal cycle, easterly wave location, and rain
thresholds can be found in Schumacher et al. (2007).
The location of the radar and sounding sites and the
variational analysis domain for KWAJEX are shown in
Fig. 1. Kwajalein Island is east of the center of the
variational analysis domain, which has a radius of about
85 km. This radius makes the KWAJEX variational
analysis area small (24 341 km2) compared to other
studies [cf. ⬃80 000 km2 over the B-scale network in
the Global Atmospheric Research Program (GARP)
Atlantic Tropical Experiment (GATE; Thompson et al.
1979), ⬃217 000 km2 in Reed and Recker’s (1971) west
Pacific analysis, and ⬃225 000 km2 over the intensive
flux array in Tropical Ocean and Global Atmosphere
Coupled Ocean–Atmosphere Response Experiment
(TOGA COARE; Lin and Johnson 1996)]. Because
Rain rate
(mm day⫺1)
2.0
2.6
17.1
2.3
4.3
7.4
8.7
6.2
6.5
measurement errors averaged over a small domain are
typically larger than those averaged over a large domain, the uncertainties of the heating profiles for
KWAJEX should be large compared to other studies.
In addition, sampling errors for KWAJEX should be
large compared to other studies, because the sampling
errors decrease with averaging scale (Mapes et al.
2003). However, a smaller budget area should be more
conducive to analyzing heating profiles of individual
cloud types. In addition, visibility was generally very
good during KWAJEX such that cloud observations of
mid- and high-level clouds and tall cumulus towers
were possible though much of the region. Even on days
with large particle haze, visibility was still in the tens of
kilometers (A. Rangno 2007, personal communication;
see also Rangno and Hobbs 2005). Finally, it is assumed
that the cloud field does not vary significantly over the
domain at each observation time because the region is
effectively open ocean and would not be expected to
show large spatial variability in forcing. Thus, the cloud
observations from Kwajalein Island are considered to
be generally representative of the variational analysis
domain.
TABLE 3. KWAJEX cloud types with high-level bases.
CH
Description
Priority
No. of
observations
Frequency
(%)
Rain rate
(mm day⫺1)
0
1
2
3
4
5
6
7
8
9
/
No clouds with bases above 400 hPa
Cirrus (Ci) filaments not invading the sky
Dense Ci patches or Ci with turrets
Dense Ci anvil remnants
Ci filaments invading the sky
Ci and cirrostratus (Cs) or Cs alone invading the sky, ⬍45° above horizon
Ci and Cs or Cs alone invading the sky, ⬎45° above horizon
Cs covering celestial dome
Cs not invading sky and not covering entire dome
Cirrocumulus (Cc) predominant
Upper levels obscured by lower clouds
8
7
7
6
5
4
4
2
3
1
/
10
17
8
13
3
15
22
9
23
20
13
6.5
11.1
5.2
8.5
2.0
9.8
14.4
5.9
15.0
13.1
8.5
2.0
1.7
2.2
4.7
5.8
6.8
5.1
7.0
3.2
23.3
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3. Results and discussion
a. Cloud-type occurrence
Cloud observations began the afternoon of 25 July
and ended the evening of 14 September. A total of 153
daytime cloud observations will be used in the following analysis. Tables 1–3 list the number of observations
and frequency of occurrence of each cloud type with
bases at low, mid-, and high levels, respectively. Figure
2 shows photographs taken during KWAJEX of fairweather cumulus, cumulus congestus, and cumulonimbus clouds, which were the most commonly observed
cloud-type bases during the experiment.
Table 1 shows that negligible counts of CL 0, 4, 5, 6,
and 8 were observed during KWAJEX; that is, there
was rarely an absence of clouds with low-level bases
(CL 0), and stratus (St) and stratocumulus (Sc) (CL 4–6
and 8) were seldom reported, although stratus (and/or
cumulus) fractus of bad weather (CL 7) accounted for
7% of the observations. Cumulonimbus (Cb; CL 3 and
9) was observed 39% of the time followed by cumulus
congestus (TCu; CL 2), which accounted for 31% of the
observations, and fair-weather cumulus (Cu; CL 1),
which accounted for 22% of the observations. Note that
Cb, TCu, and Cu may coexist with one another, but that
the synoptic code gives priority to more developed lowlevel clouds. This synoptic prioritization presents a limitation to the current study, so the reader should be
aware of the possibility of lower-priority clouds contributing to the heating profiles of higher-priority
clouds. The KWAJEX low-cloud distributions are generally consistent with the June–August (JJA) cloud climatology in Norris (1998), although Norris’s climatology showed slightly lower occurrences of Cb and Cu in
the Kwajalein region. The predominance of Cu, TCu,
and Cb during KWAJEX is also consistent with the
TOGA COARE observations from Johnson et al.
(1999) of a trimodal convective cloud distribution over
the tropical ocean.
Table 2 shows that no midlevel clouds (CM 0) were
observed about a quarter of the time. Altostratus (As;
CM 1 and 2) was relatively rare, with an occurrence of
7% for semitransparent clouds and 10% for thicker
clouds or nimbostratus (Ns). These two cloud types
have the highest priority for midlevel clouds. Altocumulus (Ac; CM 3–9) was observed 60% of the time.
Table 3 shows that no high clouds (CH 0) were seen
7% of the time during KWAJEX, while upper levels
were obscured (CH /) 9% of the time. Cirrocumulus
(Cc; CH 9) occurred in 13% of the observations and
cirrostratus (Cs) not invading the sky (CH 7 and 8) was
observed 20% of the time. These three designations
FIG. 2. Photographs of cloud types with low-level bases taken
from the KWAJEX operations center: (a) fair-weather cumulus
(0600 UTC 21 Aug), (b) cumulus congestus (0100 UTC 4 Aug),
and (c) cumulonimbus (2000 UTC 14 Sep). (Images courtesy of
the University of Washington.)
have the highest priority for high-level clouds. Cirrus
(Ci) or Cs invading the sky (CH 4–6) accounted for
about a quarter of the observations, while other Ci
types (CH 1–3) were present in the other quarter of the
high-cloud observations.
b. Cloud-type rain rates
Tables 1–3 also show the average rain rate observed
by the Kwajalein radar over the variational analysis
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SCHUMACHER ET AL.
domain during the 6-h period encompassing each cloud
observation (e.g., 2100–0300 UTC rain rates for 0100
UTC cloud observations). Rain rates were not calculated for cloud types with less than eight counts (i.e.,
⬍5% of the observations).
The rain rates in Table 1 appear consistent with the
low-level cloud-type designations. For example, when
Cu (CL 1) was the only evident low-level cloud, the rain
rate was low (0.8 mm day⫺1). As the clouds grew in
vertical extent from TCu (CL 2) to Cb (CL 3 and 9), the
rain rate increased from 3.1 to 8.0 mm day⫺1. Based on
aircraft observations during KWAJEX, Rangno and
Hobbs (2005) showed that cumulus clouds began to
precipitate once they reached 1.5 km in depth (i.e., the
depth that Cu begins transitioning to TCu) and that the
collision–coalescence process was especially robust in
congestus clouds, which is consistent with the higher
TCu rain rate. When St or Cu fractus of bad weather
(CL 7) was present, the rain rate was 28.3 mm day⫺1,
which is consistent with significant rain production by
tropical convective systems that cover extensive areas.
Midlevel cloud types also show a coherent link to
rain production (Table 2). Lower rain rates (⬍5 mm
day⫺1) occurred when midlevel clouds were absent (CM
0) or when the midlevel clouds were semitransparent
As or Ac (CM 1, 3, and 4). Moderate rain rates (6–9 mm
day⫺1) occurred when thicker Ac (CM 6–9) was present.
The highest rain rate (17.1 mm day⫺1) occurred when
thick As or Ns (CM 2) was observed.
At upper levels (Table 3), lower rain rates (⬍5 mm
day⫺1) occurred either when no ice clouds (CH 0) were
visible or in the presence of Ci (CH 1–3) or Cc (CH 9).
Moderate rain rates (5–7 mm day⫺1) occurred when Cs
(CH 5–8) was observed. The highest rain rate (23.3 mm
day⫺1) occurred when the upper levels were obscured
(CH /) most commonly by Ns (CM 2) or multilayer Ac
(CM 7).
c. Cloud-type Q1
The average Q1 profile during KWAJEX is shown in
Fig. 3. The main heating maximum is 1.8 K day⫺1 at 550
hPa, with a secondary heating maximum of 1.5 K day⫺1
at 750 hPa (see also Schumacher et al. 2007). The daytime Q1 profile (i.e., the times when cloud observations
were made) and the difference between the two profiles
are included to show that there is a sampling bias of
upper-level heating centered around 350 hPa and
lower-level heating near the surface using only observations during daylight hours. This bias is likely due to
the diurnal variation in shortwave heating (Mather et
al. 2007), but could also be caused by variations in both
cloud cover and type.
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FIG. 3. KWAJEX Q1 profiles for all observations, daytime-only
(1800, 0000, and 0600 UTC) observations, and the difference between daytime and all times.
The average Q1 profile for each cloud type is shown
in Fig. 4. As with the rain-rate calculation, cloud observations were matched with the Q1 profile computed for
the 6-h period encompassing the cloud observation. It
should be noted that other cloud types also contribute
to each heating profile [see Warren et al. (1985) for
more discussion about simultaneous cloud-type occurrence], but that the plotted profile best represents the
average conditions associated with the presence of that
particular cloud. In addition, Q1 represents condensational, radiative, and vertical eddy sensible heat effects,
and these effects may vary substantially from one cloud
type to the next. The Q1 profiles in Fig. 4 are broadly
separated by rain rates, with low rain-rate (⬍5 mm
day⫺1) cloud types in the left panels, moderate rain-rate
(5–9 mm day⫺1) cloud types in the middle panels, and
high rain-rate (⬎17 mm day⫺1) cloud types in the right
panels. Uncertainties in the Q1 analysis are estimated to
be dominated by, and similar to, those in surface precipitation (Zhang et al. 2001). Thus, stratification of the
Q1 profiles by rain rates should reduce the uncertainties
in the amplitudes of the Q1 profiles that are associated
with the rain-rate bins resulting from the variational
constraints. In addition, profiles are not shown for
cloud types accounting for ⬍5% of the observations
(i.e., ⬍eight counts) during the field campaign to avoid
the large uncertainties related to sampling error
(Mapes et al. 2003).
The Cu (CL 1) Q1 profile (Fig. 4a, left panel) exhibits
heating below 850 hPa and cooling up to 275 hPa. The
profile has a maximum heating of 1 K day⫺1 near the
surface and a maximum cooling of 1.7 K day⫺1 at 450
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FIG. 4. Average Q1 profiles for each cloud type during KWAJEX. (left) Low (⬍5 mm day⫺1), (middle) moderate (5–9 mm day⫺1),
and (right) high (⬎17 mm day⫺1) rain-rate cloud types are shown. (a) CL: (left) Cu and TCu, (middle) Cb, and (right) St and/or Cu
fractus of bad weather; (b) CM: (left) semitransparent As and Ac, (middle) thick Ac, and (right) Ns; and (c) CH: (left) Ci and Cc,
(middle) Cs, and (right) upper levels obscured.
hPa. A secondary heating maximum occurs at 175 hPa.
The lower part of this profile is similar to the undisturbed trade wind cumulus Q1 profiles in the west Atlantic (Nitta and Esbensen 1974), except that the cooling around 800 hPa (most likely resulting from evaporation of detrained cloud material) is less pronounced
in the CL 1 profile because a strong trade wind inversion was not as prevalent during KWAJEX. The midto upper-level cooling near 450 hPa is likely associated
with clear-sky radiative cooling, while the upper-level
heating peak at 175 hPa likely reflects the radiative
effects resulting from the presence of cirrus clouds and
is observed in many of the cloud-type profiles in Fig. 4.
To further investigate the probable radiative effect at
upper levels, Fig. 5 shows the diurnal variation of the
CL 1 Q1 profile. Note that there was an equal occurrence of a CL 1 at each time. Note also that the columnintegrated values of the radiative component of diabatic heating QR during KWAJEX were ⫺1.2, 0.3, and
⫺0.8 K day⫺1 for 0600, 1200, and 1800 LT, respectively
(Schumacher et al. 2007). In Fig. 5, the 0600 LT profile
is similar to the average CL 1 profile, but it is shifted left
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SCHUMACHER ET AL.
FIG. 5. Diurnal Q1 profiles for fair-weather cumulus (CL 1)
observations during KWAJEX.
in part because QR is more negative in the morning
than in the afternoon or early evening. The 1200 LT
profile is similar to the 0600 LT profile at low levels, but
the heating above 500 hPa suggests strong daytime solar absorption by the tropical atmosphere along with
the high clouds commonly observed with fair-weather
cumulus. The 1800 LT profile shows heating between
900 and 600 hPa, which is suggestive of more vertically
developed clouds. In addition, the 1800 LT profile
shows cooling at 450 hPa that is similar in magnitude to
the morning. However, the 1800 LT profile shows more
cooling above this level, suggesting different upperlevel cloud coverage, height, and/or thickness than at
0600 LT. Figure 5 is generally consistent with the strong
diurnal cycle in QR at upper levels observed by Mather
et al. (2007) when high clouds are present over Manus
Island in the west Pacific.
The TCu (CL 2) Q1 profile (Fig. 4a, left panel) exhibits heating on the order of 1 K day⫺1 from the surface to 575 hPa and cooling from 575 to 225 hPa, with
a maximum cooling of 0.8 K day⫺1 near 450 hPa. A
simple Student’s t test shows that the CL 1 and CL 2
profiles are significantly different between 700 and 525
hPa. The deeper heating in the cumulus congestus profile indicates an enhanced latent heat release in more
vertically developed clouds, while the cooling aloft is
likely a mix of evaporative and radiative cooling. The
diurnal variation in the CL 2 (not shown) indicates
weak upper-level cooling at 0600 LT, heating aloft at
1200 LT, and strong upper-level cooling at 1800 LT,
also in general agreement with Mather et al.’s (2007)
upper-level QR calculations in cloudy skies. Further,
the average CL 2 profile is consistent with Nitta and
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Esbensen’s (1974) 28 June Q1 profile, which captured
disturbed trade wind conditions with clouds extending
well above the trade wind inversion. The low-level
heating peak around 800 hPa also coincides with the
heating maximum of the initial stage in the life cycle of
a tropical cloud cluster during GATE, when deep convection is minimal (Frank and McBride 1989), and of
the second principal component of the TOGA COARE
intensive flux array Q1 (Tung et al. 1999). However,
neither of these profiles indicated cooling aloft.
The Cb (CL 3 and 9) Q1 profiles (Fig. 4a, middle
panel) are almost identical and exhibit heating throughout the depth of the troposphere, with maxima of ⬃3.7
K day⫺1 at 550 hPa. This deep heating is consistent with
the large vertical extent and heavy rain rates of cumulonimbus clouds. The heating maximum in the St and/
or Cu fractus of the bad weather (CL 7) Q1 profile (Fig.
4a, right panel) is at a similar height as in the Cb profiles, but it is almost 5 times greater in magnitude, with
more heating above the peak. Half of the CL 7 observations occur in conjunction with Ns, which is indicative
of widespread convection and rain (i.e., a conglomeration of Cbs and resultant stratiform rain rather than just
a handful of individual cells), and thus large Q1 values.
The CL 7 profile is also consistent with past budget
studies of large tropical convective systems (Reed and
Recker 1971; Yanai et al. 1973; Frank and McBride
1989, etc.).
When no clouds with bases at midlevels are present
(CM 0), Cu and TCu are observed 90% of the time.
Therefore, the CM 0 Q1 profile (Fig. 4b, left panel) is
roughly an average of the CL 1 and CL 2 Q1 profiles,
with weak heating below 750 hPa and stronger cooling
aloft. Semitransparent patches of Ac continually changing in appearance (CM 4) occur three-quarters of the
time with TCu, such that the CM 4 Q1 profile is similar
to the CL 2 Q1 profile, but with enhanced heating between 800 and 600 hPa, which is within the height range
ascribed to CM clouds. The other semitransparent Ac
cloud category (CM 3), in which the clouds are only at
one level and are unchanging in appearance, has a Q1
profile that is somewhat opposite of the other low rainrate cloud types, with cooling up to 1 K day⫺1 below
700 hPa, weak heating increasing from 700 to 400 hPa,
and heating ⬎1 K day⫺1 above 400 hPa (although there
is a shallow heating layer near the surface associated
with Cu). The heating above 400 hPa is possibly associated with the common occurrence of Cc with this
cloud type. The semitransparent As (CM 1) Q1 profile
exhibits a heating peak of 1.5 K day⫺1 at 550 hPa, the
level at which these clouds roughly occur, with a secondary heating peak of 0.5 K day⫺1 at 900 hPa from Cu
and TCu.
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MONTHLY WEATHER REVIEW
The thicker Ac (CM 6–9) Q1 profiles (Fig. 4b, middle
panel) show heating throughout the troposphere, but
with varying heights of maximum heating. Altocumulus
from the spreading out of cumulus (CM 6) has a Q1
profile with a broad heating maximum of 2.3 K day⫺1
from 850 to 750 hPa. This cloud category occurs in
conjunction with Cb 80% of the time, but the lower
heating peak may indicate a preferred layer for detrainment (Zuidema 1998). Altocumulus with turrets (CM 8)
has an even broader heating maximum of 2.7 K day⫺1
from 750 to 550 hPa. Altocumulus in multiple layers or
in the presence of Ns (CM 7) has the most elevated
heating of 4 K day⫺1 at 500 hPa. The Q1 profile representing the Ac of a chaotic sky (CM 9) is a blend of the
other three Ac profiles in the middle panel. Dense As
or Ns (CM 2) has a Q1 profile (Fig. 4b, right panel) with
maximum heating of 10 K day⫺1 at 550 hPa, 2.5–4 times
greater than other midlevel cloud types.
Similar to the absence of midlevel clouds, the absence of clouds with bases at high levels often occurs
when Cu or TCu are present (i.e., 70% of the time) such
that the CH 0 Q1 profile (Fig. 4c, left panel) is an average of the CL 1 and CL 2 Q1 profiles. A similar argument can be made for when Ci filaments (CH 1) predominate such that this cloud type does not appear to
have a large impact on Q1. The presence of Ci patches
or cumuliform tufts (CH 2) is associated with little vertical structure in Q1, while the presence of dense anvil
remnants of Cb (CH 3) is linked to sizeable heating (up
to 2 K day⫺1) above 600 hPa, possibly indicating significant cloud radiative forcing at upper levels. When Cc
predominates (CH 9), the maximum heating is lower
(around 650 hPa) and weaker (1.3 K day⫺1), likely because Cc occurs 25% of the time with turreted Ac (CM
8), which also has maximum heating around that height.
However, there is a secondary heating maximum near
300 hPa.
Cirrostratus designations (CH 5–8) indicate variations in the cover and progression of cirrostratus across
the sky. The associated Q1 profiles (Fig. 4c, middle
panel) show heating on the order of 2–3 K day⫺1
through much of the lower and midtroposphere, which
suggests that Cs is associated with vertical variations in
Q1 via the low- and midlevel clouds with which it occurs. Cirrostratus invading the sky (CH 5 and 6) has
more low-level heating, perhaps being associated with
developing convection, while Cs not invading the sky
(CH 7 and 8) has more elevated heating associated with
more mature convection. Each Cs designation shows a
secondary Q1 peak between 400 and 300 hPa, except for
CH 7. The lack of an upper-level CH 7 heating peak is
likely because this cloud type was most commonly observed at 1800 LT, when QR is negative. CH 8, which
VOLUME 136
FIG. 6. Average KWAJEX cloud-type Q1 profiles grouped by
category.
has the strongest upper-level Q1 peak, was observed
much more often at 1200 LT, a time when shortwave
radiative heating dominates. When upper levels are obscured (CH /), the Q1 profile (Fig. 4c, right panel) resembles the CL 7 and CM 2 profiles of strong, deep
heating.
Figure 6 synthesizes Fig. 4 by averaging Q1 profiles
for similar cloud types in the left and middle panels. As
previously discussed, Cu and TCu (CL 1 and 2) are
associated with relatively weak heating at low levels
and slightly stronger cooling in the mid- to upper troposphere. In aggregate, semitransparent As and Ac
(CM 1, 3, and 4) are associated with heating on the
order of 0.5 K day⫺1 in the middle troposphere. Both Ci
and Cc (CH 1–3 and 9) appear to have a weak heating
signal above 400 hPa. The presence of Cb (CL 3 and 9)
is associated with the largest heating throughout the
troposphere, although thick Ac (CM 6–9) is also associated with strong tropospheric heating, in part because
these midlevel clouds commonly occur with Cb. Cirrostratus (CH 5–8) has a weak-to-moderate heating signal
in the upper troposphere in addition to stronger heating
below 400 hPa associated with other cloud types.
d. CL divergence and Q2
While this study is primarily focused on diabatic
heating profiles associated with the various cloud types
observed during KWAJEX, tropical cloud systems are
also strongly linked to the large-scale circulation and
tropical atmosphere via divergence (Mapes and Houze
1995) and moistening (e.g., Reed and Recker 1971).
Figure 7 shows the horizontal divergence and apparent
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SCHUMACHER ET AL.
FIG. 7. KWAJEX profiles of (a) divergence and (b) Q2 for all
observations, daytime-only (1800, 0000, and 0600 UTC) observations, and the difference between daytime and all times.
moisture sink (or Q2) profiles calculated from the variational analysis for all observations, as well as daytimeonly observations, during the field campaign. Yanai et
al. (1973) defined Q2 as
Q2 ⫽ ⫺L
冉
冊
⭸共q ␻兲
⭸q
,
⫹ ⵱ ⭈ 共qV兲 ⫹
⭸t
⭸p
共2兲
where q is the specific humidity.
The average divergence profile in Fig. 7a indicates
convergence below 650 hPa and divergence aloft with a
maximum divergence value of 0.2 ⫻ 10⫺5 s⫺1 at 500
hPa. A secondary peak in divergence occurs at 175 hPa
and a relative minimum in the low-level convergence
occurs at 900 hPa. This profile suggests convective
4297
cloud populations with characteristic tops near 900, 500,
and 175 hPa, similar to the horizontal divergence profile observed in the east Atlantic during GATE by
Thompson et al. (1979) and consistent with Johnson et
al.’s (1999) work on the trimodal distribution of oceanic
convective clouds. However, the upper-level divergence peak in the KWAJEX profile is closer in height
to the higher divergence peak observed in the west Pacific by Reed and Recker (1971), suggesting deeper
convection than over the east Atlantic.
The average Q2 profile in Fig. 7b indicates apparent
drying (positive values) throughout the troposphere
with magnitudes of 1–1.5 K day⫺1 (similar to the Q1
magnitudes in Fig. 3) below 625 hPa and decreasing
apparent drying aloft. There is also a relative minimum
of drying at 850 hPa. This profile is generally consistent
with the average Q2 profiles observed during GATE
(Thompson et al. 1979) and TOGA COARE (Lin and
Johnson 1996); however, there is significant variation in
the heights and relative magnitudes of the drying peaks
between the field campaigns.
As in Fig. 3, the daytime profiles (i.e., the times when
cloud observations were made) and the difference between daytime and all observations for divergence and
Q2 are included in Fig. 7 to investigate any sampling
biases. In Fig. 7a, there is a tendency for weaker convergence at the surface and weaker divergence from
900 to 300 hPa during daylight hours, but the differences appear to be negligible. In Fig. 7b, there is more
apparent moistening (negative values) below 775 hPa
and slightly more apparent drying through the rest of
the troposphere in the daytime observations. The daytime bias in Q2 is slightly larger at low-levels compared
to Q1 (Fig. 3), possibly because of stronger vertical
eddy transports of moisture near the surface. However,
the daytime bias in Q1 is much more significant at upper levels where shortwave heating effects predominate.
Figure 8 shows divergence and Q2 profiles for CL
cloud types observed during KWAJEX. The Cu (CL 1)
divergence profile (Fig. 8a, left panel) exhibits divergence below 450 hPa and convergence above 450 hPa,
consistent with the concept that fair-weather cumulus
clouds commonly occur in the presence of large-scale
subsidence (Nitta and Esbensen 1974). The TCu (CL 2)
divergence profile indicates a shallow layer of strong
convergence from the surface up to 900 hPa, with
weaker convergence up to 800 hPa. Divergence exists
between 800 and 400 hPa, with convergence again
above 400 hPa. Strong low-level convergence capped
by a deeper divergence layer is consistent with a population of convective clouds detraining at varying heights
in the midtroposphere.
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FIG. 8. Profiles of (a) divergence and (b) Q2 for convective cloud types observed during KWAJEX.
The Cb (CL 3 and 9) divergence profiles (Fig. 8a,
middle panel) have convergence from the surface to
650 hPa and divergence throughout the rest of the midto upper troposphere with a peak near 500 hPa. Maximum convergence and divergence values are approximately 0.4 10⫺5 s⫺1, which is 2–3 times the value of the
less vertically developed CL 1 and CL 2 cloud types.
While the CL 3 and CL 9 Q1 profiles in Fig. 4 are almost
identical, more variation is seen in the divergence profiles in Fig. 8. Cumulonimbus clouds with ill-defined
tops (CL 3) appear to have a stronger convergence–
divergence couplet in the vertical than Cb with welldefined cirriform tops (CL 9), although the difference
between the profiles is only marginally statistically significant at 700 and 500 hPa. Stratus and/or Cu fractus of
bad weather (CL 7) has the strongest and deepest region of convergence with values of up to 0.8 10⫺5 s⫺1
from the surface to 525 hPa (Fig. 8a, right panel), with
even stronger divergence aloft. The convergence peak
near 600 hPa may be evidence of melting layer convergence in deep convective systems arising from extensive
regions of stratiform rain (Mapes and Houze 1995).
The Cu (CL 1) Q2 profile (Fig. 8b, left panel) shows
a peak in moistening at 800 hPa that can be attributed
to the upward transport of moisture by shallow cumulus
clouds (Nitta and Esbensen 1974). This peak is also
comparable to the low-level apparent moistening observed by Johnson and Lin (1997) during convectively
suppressed, light-wind periods in the equatorial west
Pacific. Moistening rates are larger than heating–
cooling rates for the Cu clouds, which is also consistent
with the results of Nitta and Esbensen (1974). A secondary peak in moistening above 600 hPa occurs when
the Cu clouds deepen at 1800 LT (as discussed in section 3c; see Fig. 5). The TCu (CL 2) Q2 profile also
indicates two moisture source peaks—a lower peak at
850 hPa and a second peak at 475 hPa. The CL 2 categorization does not preclude the presence of more
shallow clouds, such that the CL 2 Q2 profile possibly
represents the moistening effects of both cloud types,
with the lower peak being associated with detrainment
from shallow cumulus and the higher peak being associated with detrainment from cumulus congestus.
The Cb (CL 3 and 9) Q2 profiles (Fig. 8b, middle
panel) show drying throughout the troposphere. Again,
the two profiles are not as similar as in Q1. More generally, Lin and Johnson (1996) and Johnson and
Ciesielski (2000) have shown that the Q2 profiles have
more variability than the Q1 profiles. The CL 3 Q2 profile has a sharp peak at 750 hPa, whereas the CL 9
profile has a broader region of drying from 900 to 500
hPa. Cumulonimbus clouds with ill-defined tops appear
NOVEMBER 2008
4299
SCHUMACHER ET AL.
to preferentially create a larger apparent moisture sink
in the lower troposphere, although the statistical significance of the difference at 750 hPa is not strong. The
St and/or Cu fractus of bad weather (CL 7) Q2 profile
(Fig. 8b, right panel) also shows drying throughout the
troposphere, but is higher in magnitude with more drying aloft. The bottom heaviness in the Cb (CL 3 and 9)
Q2 profiles and the top heaviness in the CL 7 Q2 profile
are consistent with Johnson’s (1984) postulation that
the double peak of drying often observed in profiles of
the apparent moisture sink in the tropics occurs from
two different processes, that is, lower-level drying in
convective updrafts and upper-level drying from mesoscale updrafts in stratiform rain regions. In addition, the
local minimum at 600 hPa in the CL 7 Q2 profile may be
explained by an inflection in the specific humidity profile that can be traced to the effects of melting near the
0°C level (Johnson et al. 1996).
4. Conclusions
KWAJEX cloud distributions show a predominance
(i.e., at least a 50% occurrence) of low-level cumulus,
midlevel altocumulus, and upper-level cirrus and cirrostratus cloud, which is consistent with the expected
cloud population over an ocean ITCZ location based
on published cloud climatologies (e.g., Norris 1998).
Cloud types can be associated with certain ranges of
rain accumulations. For example, when only Cu occurs
at low levels, very low rain rates (⬍1 mm day⫺1) result,
whereas when Ns occurs at midlevels, very high rain
rates (⬎15 mm day⫺1) result. Cumulonimbus, thick Ac,
and Cs cloud observations are associated with moderate (5–9 mm day⫺1) rain rates.
Variations in cloud type with rain rate translate into
variations in the vertical structure of Q1. Small Cu
clouds produce very little rain and thus do not provide
much net heating to the atmosphere, but they can redistribute heat at low levels, as this study shows. Cumulus congestus provides deeper heating (up to 575
hPa), but still exhibits cooling aloft; Cb heats the depth
of the troposphere, with a maximum of a few Kelvin per
day near 550 hPa; and Ns provides heating at even
higher heights and greater magnitudes (on the order of
10 K day⫺1). Other mid- and high-level cloud types
show enhancement of the Q1 profile at their height of
occurrence, although high-level clouds tend to have the
weakest signal. The diurnal variation of cloud occurrence can also affect average Q1 profiles. While these
results seem intuitive, this study quantifies them by isolating a budget-calculated Q1 by cloud type. This study
also examines the divergence and Q2 profiles of con-
vective cloud types. Low-level convergence strengthens
and deepens as convective clouds become more vertically and areally extensive, while the divergence near
cloud top strengthens and narrows as it occurs at progressively higher heights. Both Cu and TCu tend to
moisten the atmosphere, while Cb and CL 7 (which is
often associated with Ns) account for more bottom- and
top-heavy drying, respectively. Explicit knowledge of
heating, divergence, and moistening parsed by cloud
type is a useful step in understanding how tropical convection interacts with phenomena such as tropical
waves and large-scale oscillations (Mapes et al. 2006).
This knowledge can also be used to improve satellite
retrievals of heating profiles (Tao et al. 2006) and validate general circulation model depictions of vertical
cloud structure (Williams and Tselioudis 2007).
Acknowledgments. Much appreciation to the
KWAJEX Ops Center groups, whose members performed the daily cloud observations. Three anonymous
reviewers provided useful comments. This research was
supported by the NASA New Investigator Program and
NSF Grant ATM-0449782 to Texas A&M University,
NASA Grant NNG04GA22G to Colorado State University, and the DOE ARM program and NSF Climate
Dynamics program to Stony Brook.
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